Articles by: "Jürgen Galler, CEO and Founder — 1plusX"

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DMPs and SSPs joining forces: a new trend in the privacy era

April 20, 2022 Jürgen Galler, CEO and Founder — 1plusX

Digital advertising needs to be rebuilt and reinvigorated. Consumers want better privacy protection, engaging content, and an overall foundation built on trust and transparency to ensure loyalty. To achieve this, data management platforms (DMPs) and supply-side platforms (SSPs) are joining forces.

As we enter the privacy-centric era of digital advertising, third-party cookies will be replaced by first-party data, which is even more powerful and effective because the signals originate directly from a publisher’s page, works on every browser, and doesn’t require third-party syncs.

In the privacy-centric era, first-party data will be the new currency for digital advertising.

Overcoming the third-party data challenge

The deprecation of third-party cookies and the need for better audience consent for cross-domain and cross-app targeting demands that publishers and advertisers put privacy at the center of everything. Publishers, like consumers, want control of their data.

By replacing third-party cookies with first-party data solutions, the combination of a DMP and an SSP will deliver that control, keep privacy at the center of business, and help to unlock the full potential of their inventory — including deeper audience insights. This deeper view will not only benefit publishers, but it will make it easier for advertisers and their DSPs to target and reach their audiences more accurately across mobile, web, and connected TV.

DMPs and SSPs are more powerful together

When leading DMPs and SSPs combine their valuable media and data capabilities, it makes for a powerful combination that will raise the fortunes of publishers and advertisers alike.

In March, TripleLift announced that it acquired our company, 1plusX. This supply-side platform bought a first-party data management platform to activate first-party data to help its publisher partners better monetize their inventory once third-party cookies are phased out. This is the first acquisition in the company’s history, which speaks to the importance placed on privacy and identity, and the confidence SSPs have in partnering with DMPs built for the privacy era. Combining a scaled SSP and a savvy DMP is a pathway forward for thousands of publishers and ad buyers. This acquisition has created that pathway.

TripleLift is not the only SSP that is planning for our industry’s privacy-centric future. Earlier this year, Magnite announced that it acquired Carbon, a platform that enables publishers to measure, manage and monetize audiences. Other partnerships aim to bridge the gap between consumer identity and the privacy-first web. As a result, publishers and advertisers will get more accurate data for campaign targeting without the need for third-party cookies or mobile ad IDs. Buyers and sellers would then in theory be able to transact based on consumer insights without data leakage or scale reduction.

Mergers and acquisitions will lead the way in MarTech

Companies everywhere are looking to accelerate their ability to fill the gap that the depreciation of third-party cookies will create. Bringing together the power of media and data, as happens when DMPs and SSPs join forces, is just one way that M&A will lead the way. As time marches on and we approach the end of third-party cookies as we know it, we will see mergers and acquisitions among independent MarTech and AdTech companies accelerate. And it will be the mergers and acquisitions that prioritize privacy and first-party data that will win the day. Because in a world without third-party cookies, if your data strategy isn’t a first-party one, then what data strategy do you really have?

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Advertising | Perspectives | Supporter Spotlight

Why prioritizing personalization can build trust between consumers and brands

January 10, 2022 Jürgen Galler, CEO and Founder — 1plusX

The pandemic era has altered consumer behavior like never before. With lockdown restrictions mandating stay-at-home orders and closing physical stores, every company — big and small — had to rethink its customer engagement strategies. This digital transformation and the mobile shift were quicker than expected. But consumers’ expectations have also radically changed in that time frame.

In an instant, consumers wanted brands to offer an enhanced user experience, especially when it came to mobile usage and ecommerce. To meet this demand, they expect companies to know who they are, what they like, and everything in between, regardless of which channel they came from. This anticipation of a more value-added exchange will only continue to rise. It’s therefore paramount that brands are ready to deliver a more personalized experience — and that publishers are empowered to help them deliver.

Start with first-party data

With first-party data, a more personalized experience can become a reality. The average buyer is becoming increasingly aware of how companies collect and use their personal data. However, they’re also demanding the highest level of privacy and security. And this trust is crucial in maintaining customer loyalty and retention.

When deciding on which brand to choose, 55% of consumers say trustworthiness and transparency are the most critical factor. Finding the sweet spot between convenience and privacy is therefore important to nurturing that relationship for a long-term future. After all, 48% of consumers appreciate the convenience of personalization as long as their data isn’t compromised.

We know that third-party cookies and comprehensive third-party data collection will most likely become obsolete. As a result, the businesses that invest and implement first-party data strategies will stay ahead of the pack.

But this isn’t necessarily straightforward. The average person touches their smartphone 2,617 times a day. They switch between an average of three devices to finish a task. And, 86% of shoppers regularly hop between two channels. However, with data silos and poor infrastructure, the necessary context to bridge these channels and build a more complete picture is missing.

Personalization for omnichannel experiences

Fuelled by the pandemic, omnichannel shopping grew by 50% in 2020. This means that consumers have become more savvy about where and how they shop online than ever before.

Nielsen also found that consumers use online channels to purchase goods, research and identify physical stores. When examining levels of engagement across channels, 56% of online shoppers put careful consideration into each purchase at the point of sale in September 2020, compared with 51% of brick-and-mortar shoppers. In addition, the average buyer is now more used to going between the physical and digital world.

Consumers now expect a seamless transition across every touchpoint they have with a company. Therefore, prioritising creation of an omnichannel experience will help increase overall ROI. This is especially true when behavioral data is used. Behavioural data provides a more personalized experience online and offline, as well as giving a boost to brand loyalty and engagement. By tracking online data and leveraging it across all channels, a better user experience is entirely possible.

Enter data management platforms

In an increasingly privacy-driven and restrictive data collection environment, the proper data infrastructure can supercharge a company’s first-party data, all while staying privacy compliant.

This is where marketing needs to get deeper into single properties. For example, richer, more granular profiles for audience targeting allows for better personalization. So often, when we do a data interview with customers at 1plusX, we realize that typically they only have robust, deterministic data or attributes that are targetable for a fraction of their use. A data infrastructure with intelligent AI and predictive capabilities can enable brands to enrich and enhance their first-party data.

By expanding their dataset, companies can better personalize services and experiences. They can offer better advertising. They can understand which user might want a subscription or be more inclined to add a product to the cart. This behavior then feeds back to brands to better understand their customers. These data insights will prove valuable to optimize and enhance their marketing efforts.

Prioritizing personalization for the future

When companies use a data management platform that puts the control of user data in their own hands, they empower the consumer. This helps build the trust and transparency needed to maintain loyalty and engagement.

As a result, companies that can bring a more personalized experience to their customers without compromising privacy will thrive. Those that don’t will inevitably fall behind.

Advertising | Perspectives | Supporter Spotlight

How AI can provide publishers with the identity advantage

September 29, 2021 Jürgen Galler, CEO and Founder — 1plusX

The post-cookie era of digital advertising is approaching. Google may have postponed its plan to remove third-party cookies, but the result remains the same: industry players must prepare for a huge amount of industry upheaval. Most notably, there will be a significant drop in data availability.

Publishers – with direct access to audiences and first-party data – are widely acknowledged as being best-placed to survive in the ecosystem’s data-frugal future. But having valuable first-party data at their fingertips won’t be enough for them to flourish. Moving forward, publishers must discover new ways to optimize their offerings, enhance their monetization strategies, and heighten the value of the user experience.

With technology powered by artificial intelligence (AI), publishers can harness the capabilities needed to become digital advertising’s main providers of quality, first-party data. They will also be in a position to build of scalable, privacy-safe data solutions. By combining the power of AI with valuable first party data, publishers have a significant competitive advantage.

AI helps publishers leverage their pair of aces

Publishers were already holding a pretty good hand, with content and consent their figurative aces. Publishers build trust among their regular users by generating high levels of audience engagement and loyalty through the production of editorial content. This, in turn, helps them earn consent from logged-in users to gather and use their first-party data.

Publishers’ first-party data strategies, therefore, give them a solid basis to achieve reach with known audiences. However, it is broadly acknowledged that consented data has its limits. At best, only one in 10 users are willing to share personal information, such as age and gender. However, almost a quarter (23%) are reluctant to do so regardless of how it could improve their online experience.

Consequently, optimizing reach beyond known users relies on publishers taking different approaches to data, aside from adopting log-in walls. To increase the effectiveness of their strategies, data processing and enrichment solutions driven by AI and machine learning are vital. Publishers looking to preserve the availability of their online content will find these especially advantageous. But all publishers stand to gain from their benefits.

Predictive modeling is one of the most valuable capabilities made possible by machine learning. The removal of third-party cookies will make deterministic data less accessible. However, with consent, publishers can leverage their logged-in user attributes as a robust analytical base for predictive models. These models then allow publishers to extend addressable reach with accuracy. This helps them target unknown audiences that exhibit similar attributes to their logged-in users.

The quality of these predictive models is also very high. For example, Ad Alliance – Germany’s number-one advertising sales house – achieved 70% market reach in a campaign for e-commerce company, OTTO (up from 32% for standard run of network campaigns), with 92% accuracy in age segment targeting.

Contextual is the trump card

To boost reach and engagement even further, publishers can also feed real-time contextual insights into their data solutions to enable privacy-friendly targeting. Contextual analysis upholds user rights to data privacy by utilizing inferred characteristics rather than declared ones.

AI technologies accurately predict audience preferences based on the content they consume. This information can then be used to personalize targeting and the user experience. For example, French publisher, Le Figaro, utilized 1plusX’s real-time audience targeting, contextual targeting and first impression targeting solutions to strengthen relevance, maximize impact, and enhance the user experience, all while adhering to data privacy regulations.

Bringing users’ content consumption into the mix, publishers can then use advanced AI analytics to develop precise, interest-based audience segmentation. This further improves targeting capabilities, resulting in stronger alignment between ad content, editorial content, and user intent. By leveraging data enrichment and machine learning capabilities on top of its contextual targeting tool, Le Figaro was able to deliver precise targeting solutions to connect with first-time users. As a result, the publisher generated an average campaign reach increase of 38% across campaigns from all verticals.

Publishers play a key role in shaping how the ecosystem accesses and uses first-party audience data sets. But simply being the gatekeepers of user data won’t give them the competitive edge they need. AI-powered solutions allow publishers to support privacy-centric advertising and optimize their own revenue streams.

With the enhanced capabilities of predictive modeling, publishers can make the most of their consented data and expand their reach to unknown audiences with a high degree of accuracy. By combining this with contextual data, they can deepen the personalization of the user experience and maximize the effectiveness of targeting methods with heightened relevance. Thanks to AI, publishers can ensure they have the optimal solution to identity challenges in the post-cookie era.

Advertising | Perspectives | Supporter Spotlight

We’re entering the age of prediction-based marketing

June 23, 2021 Jürgen Galler, CEO and Founder — 1plusX

Digital advertising is characterized by constant change, challenges and – fortunately – innovation.

One intriguing and enduring industry plotline is the tension between data-driven targeting and user privacy. The narrative commenced with stricter data regulations. Now, it’s reached a critical point with the deprecation of third-party cookies and reduced access to mobile advertising identifiers.

There is no real replacement for third-party cookies and mobile IDs. So, we are starting to see a patchwork of targeting solutions emerge. We won’t entirely shift away from an identity even as we edge closer to a privacy-first age. Rather, success will be determined by a combination of solutions.

Privacy has been a prominent topic for many years. So has a demand for targeting. The reality is that some sort of ID solution will continue to be used for the foreseeable future. What we’re likely to see, however, is a move from precision-based marketing to prediction-based marketing. Thus, advertisers will increasingly rely on audiences built on the basis of having the highest probability to purchase their products.

Publishers, as the gatekeepers of first-party data, are poised to take a stronger position in the digital ecosystem. This is particularly true for those supported by artificial intelligence (AI) powered predictive analytics. These solutions will allow them to make the most of that precious data and achieve the scale advertisers need.

First-party data, identity, both, or more?

Unlike most participants in the digital advertising supply chain, publishers have direct consumer contact. And their advertising partners will benefit from first-party data drawn from that interaction.

Advances in data enrichment techniques enable publishers to generate user insights directly from that first party data. This allows publishers to offer the scale and quality marketers need to achieve their goals. It is also worth noting that solutions that allow data processing and the extraction of value closer to the source of the data also reduce the risks associated with data sharing.

To make use of their first-party data for targeting purposes, publishers can begin by creating basic reach among users that are known to them through log-in details or subscriptions. They can then form larger addressable audience segments by syndicating those user profiles through identity networks and matching them to a wider identity connectivity layer using AI-powered technologies to orchestrate and consolidate their data.

While the result of this process is a pool of audience insight ready for activation, these steps will still only deliver limited reach. The reality of extracting value from first party data is that established publishers need to balance paywalls and login screens with ensuring a positive user experience. Also, without being able to tap into predictive modelling on top of their first-party data strategies, publishers will struggle to achieve true scale.

From your current targetable audience reach to 100% (really!)

AI-powered predictive modelling allows publishers to monetize their inventory through targeted advertising in a way that is privacy compliant. That’s because it relies on logical, predicted — rather than declared — attributes. To fill the gaps in their data and expand reach, publishers can use algorithms to analyze on-site activity for users that have consented to this practice. Publishers can build detailed user profiles and intricate attribute patterns that include interests, habits, and preferences.

This information can be used for advanced audience expansion. It also enables targeting users with similar profiles, even if they aren’t logged in. It can also be used to predict attributes of anonymous users, such as gender, age, and interests. By combining these privacy-compliant profiles with real-time context and content information, impressions can be made addressable without user-level data.

This approach can even be used for retargeting by matching publisher and advertiser audiences based on similarities, using clean-room technology. With a clear picture of audience trends and preferences, publishers will be able to bring 100% of users within targeting range.

Contextual Targeting supercharged and cross-platform

A third element in the mix will be contextual targeting. However, it will be a more sophisticated AI-powered version of the contextual targeting we’ve known in the past. Using advanced analytics, publishers can determine what content users are interacting with across multiple digital properties. They can use this information to unearth granular interest areas far beyond high-level keywords. Targeting against these specific interest patterns will be particularly useful for native mobile channels, as well as connected TV and podcasts. Critically, it will allow brands to reach users when they are absorbed in relevant content.

This multi-layered approach to audience targeting in a world with no third-party cookies and reduction of mobile IDs will be beneficial across the supply chain. It allows publishers to effectively monetize inventory through relevant advertising that their audiences find engaging and applicable rather than annoying and disruptive. And it can do all this while respecting user privacy. For advertisers, predictive analytics enables them to spot the most receptive audiences at every stage of their digital journey and understand where they are most likely to be next.

As the targeting vs. privacy story heads towards its culmination, industry innovation will see a multitude of targeting solutions emerge. Overall, user-level targeting will shrink and both audience-level and contextual targeting will grow. Predictive marketing powered by AI and publisher first-party data will lead the way into a new age of targeting.